The standard Affymetrix labeling and hybridization protocols were used on an ATH1 Affymetrix GeneChip microarray encompassing 22, 814 probe sets (Affymetrix Inc, Santa Clara, CA, USA).
Due to the presence of 11 different oligonucleotide sets for each specific gene being used on the microarray versus only a single primer set for a gene in a quantitative PCR, the microarray is more effective at eliminating false positive or negative data and provides a more robust quantification of changes in gene expression.
Due to the presence of 11 different oligonucleotide sets for each specific gene being used on the microarray versus only a single primer set for a gene in a quantative PCR, the microarray is more effective at eliminating false positive or negative data and provides a more robust quantitation of changes in gene expression.
To simulate the use of a microarray based on a single reference taxon, one species from each tree was chosen as the reference and only those pairwise comparisons involving the reference individual were saved, corresponding to the genetic distance from the reference species to all other taxa.
Re-defined transcript-specific probe sets were used on available microarray data of human renal tissue [9] to predict the expression of individual transcripts.
These primers were designed independently from the oligonucleotides used on the microarray.
The Contigs and singleton sequences used on the microarray were used to query GenBank's nonredundant database and the TAIR database with BLASTx.
This gene, involved in non- β-catenin Wnt signalling (Kuhl et al, 2000), has been tested with quantitative RT PCR on the same series of RNA that has been used on microarrays as an alternative method to verify array data.
Though first thought to be of ideal quality for microarray, these human lung fibroblast test samples have been shown through the application of this novel assay to be less than optimal for use on a microarray chip.
The authors compared transcript levels in filaments and in a heterocyst-enriched fraction; the multi-gene features used on the microarrays limited the interpretation of the results.
